Quantum Algorithms Simulate Heat to Create Stable Thermal States

A new method for efficiently preparing thermal states is enabling advances in fields from materials science to machine learning. Andrew Wright and colleagues at the Institute of Physics, in collaboration with Chulalongkorn University and Keio University, have developed a technique termed double-bracket thermofield double (DB-TFD) that uses double-bracket quantum algorithms to simulate thermofield double states and realise Gibbs states. The poly DB-TFD algorithm’s complexity scales favourably with inverse temperature, consistent with established techniques and confirmed by numerical simulations. Moreover, the team demonstrates DB-TFD’s potential in quantum Boltzmann machines, achieving improved performance compared with existing variational methods, and providing…